brierScore

Derives the Brier Scores (using Inverse Probability of Censoring Weighting) for the Survival estimates as detailed in (Blanche et al. 2015) .

Usage

# S3 method for SurvivalQuantities
brierScore(object, maintain_cen_order = TRUE, event_offset = TRUE, ...)

Arguments

object

(SurvivalQuantities)
survival quantities.

maintain_cen_order

(logical)
If TRUE then, in the case of ties, censor times are always considered to have occurred after the event times when calculating the "reverse Kaplan-Meier" for the IPCW estimates. Setting this to TRUE mirrors the implementation of the {prodlim} package.

event_offset

(logical)
If TRUE then \(G(T_i)\) is evaluated at \(G(T_i-)\). Setting this as TRUE mirrors the implementation of the {pec} package.

...

not used.

References

Blanche P, Proust-Lima C, Loubère L, Berr C, Dartigues J, Jacqmin-Gadda H (2015). “Quantifying and comparing dynamic predictive accuracy of joint models for longitudinal marker and time-to-event in presence of censoring and competing risks.” Biometrics, 71(1), 102-113. doi:10.1111/biom.12232 , https://onlinelibrary.wiley.com/doi/pdf/10.1111/biom.12232, https://onlinelibrary.wiley.com/doi/abs/10.1111/biom.12232.

See also

Other brierScore: brierScore()

Other SurvivalQuantities: SurvivalQuantities-class, as.data.frame.SurvivalQuantities(), autoplot.SurvivalQuantities(), summary.SurvivalQuantities()